Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 636 · 40 questions

AI tip (Accuracy = correct ÷ total × 100): Steps: 1 choose a problem → 2 collect examples → 3 label them → 4 check and correct bad labels (clean the data) → 5 split into training and test sets → 6 train → 7 test with new examples → 8 measure accuracy → 9 improve the data and retest. Accuracy = correct ÷ total × 100. Wrong = total − correct. Expected right = accuracy ÷ 100 × total. Keep some examples apart for testing (for example one fifth); the rest are for training.

1. 1.❌ Saanvi’s leaf identifier was tested on 30 new leaf photos and got 27 right. How many did it get wrong?
2. 2.🧪 Why must you test a model on examples it has NOT seen? (a) to make it faster (b) to see if it learned (c) to save paper (d) to make it bigger
3. 3.📦 Ananya collected 170 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
4. 4.🎯 Meera’s leaf identifier is 80% accurate. If it is tested on 40 new leaf photos, how many should it get right?
5. 5.🎯 Tara’s leaf identifier is 60% accurate. If it is tested on 60 new leaf photos, how many should it get right?
6. 6.🎯 Meera’s handwriting reader was tested on 25 new handwritten letters and got 24 right. What is its accuracy in percent?
7. 7.📦 Ishaan collected 200 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
8. 8.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct ÷ total × 100 (d) correct + total
9. 9.📋 Planning an AI project: which comes first — correct bad labels or label each example? (a) correct bad labels (b) label each example
10. 10.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) a new colour screen (c) more labelled examples (d) fewer examples
11. 11.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 10 right and Model B got 6 right. How many percentage points more accurate is Model A?
12. 12.🧪 You can plan a simple AI project with… (a) nothing at all (b) a secret password (c) only a big robot (d) paper and examples
13. 13.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 24 right and Model B got 23 right. How many percentage points more accurate is Model A?
14. 14.📋 Planning an AI project: which comes first — train the model or set aside test photos? (a) train the model (b) set aside test photos
15. 15.📋 Planning an AI project: which comes first — pick a question to solve or let it learn patterns? (a) pick a question to solve (b) let it learn patterns
16. 16.🎯 Kabir’s recycling sorter was tested on 4 new waste photos and got 4 right. What is its accuracy in percent?
17. 17.📋 Planning an AI project: which comes first — tag each photo by type or train the model? (a) tag each photo by type (b) train the model
18. 18.🎯 Rohan’s recycling sorter is 90% accurate. If it is tested on 20 new waste photos, how many should it get right?
19. 19.❌ Arjun’s leaf identifier was tested on 35 new leaf photos and got 32 right. How many did it get wrong?
20. 20.🎯 Tara’s fruit sorter is 60% accurate. If it is tested on 30 new fruit photos, how many should it get right?
21. 21.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 8 right and Model B got 7 right. How many percentage points more accurate is Model A?
22. 22.📋 Planning an AI project: which comes first — recheck every label or let it learn patterns? (a) recheck every label (b) let it learn patterns
23. 23.📋 Planning an AI project: which comes first — try unseen examples or label each example? (a) try unseen examples (b) label each example
24. 24.🎯 Diya’s handwriting reader is 50% accurate. If it is tested on 70 new handwritten letters, how many should it get right?
25. 25.🎯 Diya’s handwriting reader was tested on 50 new handwritten letters and got 36 right. What is its accuracy in percent?
26. 26.📋 Planning an AI project: which comes first — try unseen examples or train the model? (a) try unseen examples (b) train the model
27. 27.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
28. 28.🎯 Saanvi’s spam spotter was tested on 50 new messages and got 28 right. What is its accuracy in percent?
29. 29.📋 Planning an AI project: which comes first — tag each photo by type or try unseen examples? (a) tag each photo by type (b) try unseen examples
30. 30.📋 Planning an AI project: which comes first — tag each photo by type or improve data, retest? (a) tag each photo by type (b) improve data, retest
31. 31.🎯 Diya’s spam spotter was tested on 10 new messages and got 5 right. What is its accuracy in percent?
32. 32.📋 Planning an AI project: which comes first — test on new photos or collect fruit photos? (a) test on new photos (b) collect fruit photos
33. 33.📋 Planning an AI project: which comes first — fix it and test again or calculate percent right? (a) fix it and test again (b) calculate percent right
34. 34.📦 Kabir collected 150 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
35. 35.📋 Planning an AI project: which comes first — label each example or gather many examples? (a) label each example (b) gather many examples
36. 36.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 24 right and Model B got 16 right. How many percentage points more accurate is Model A?
37. 37.📋 Planning an AI project: which comes first — set aside test photos or correct bad labels? (a) set aside test photos (b) correct bad labels
38. 38.🎯 Nisha’s leaf identifier was tested on 4 new leaf photos and got 4 right. What is its accuracy in percent?
39. 39.📦 Meera collected 120 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
40. 40.📋 Planning an AI project: which comes first — tag each photo by type or split train and test? (a) tag each photo by type (b) split train and test

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